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Introduction Why keyword search in relational databases? We want to search text data in relational databases SQL with the “ contains ” operator is not for non-expert users Keyword search is tremendous successful in text database by ranking documents based on similarity. It is for non-expert users SIGMOD 2006: Effective Keyword Search in Relational Databases

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Introduction Let ’ s do it, but how? What are answers to be ranked? How should we rank these answers? SIGMOD 2006: Effective Keyword Search in Relational Databases

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Introduction -- an answer An answer for a given query Q: a tuple tree, in which every leaf node must have at least one keyword in Q. SIGMOD 2006: Effective Keyword Search in Relational Databases

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Introduction Use a slightly modified algorithm [DISCOVER] to produce all answers for a given query. SIGMOD 2006: Effective Keyword Search in Relational Databases

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Introduction: Ranking Our focus is on the effectiveness problem of ranking answers: the more relevant an answer is to the user query, the higher it should be ranked. SIGMOD 2006: Effective Keyword Search in Relational Databases

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Introduction: Contributions We identify four new factors that are critical to effective ranking and we propose a new ranking strategy Design and conduct comprehensive experiments for the effectiveness problem Experimental results show our strategy is significantly better than existing works in effectiveness SIGMOD 2006: Effective Keyword Search in Relational Databases

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Experiments – measure Reciprocal rank: measures how good the system is to return the first relevant answer. MAP (mean average precision): A precision is computed after each relevant answer is retrieved. Then we average all precision values to get a single number to measure the overall effectiveness.

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Conclusions Effectiveness is as important as efficiency The four new factors are critical to search effectiveness Our strategy is significantly more effective than related works SIGMOD 2006: Effective Keyword Search in Relational Databases